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[P] PyTorch Implementation of Semantic Segmentation models

Nothing fancy, but to get a handle of semantic segmentation methods, I re-implemented some well known models with a clear structured code (following this PyTorch template), in particularly:

  • The implemented models are: Deeplab V3+ – GCN – PSPnet – Unet – Segnet and FCN

  • Supported datasets: Pascal Voc, Cityscapes, ADE20K, COCO stuff,

  • Losses: Dice-Loss, CE Dice loss, Focal Loss and Lovasz Softmax,

with various data augmentations and learning rate schedulers (poly learning rate and one cycle).

I though I share this implementation in case anyone might be interested, and here it is :

Github: https://github.com/yassouali/pytorch_segmentation

submitted by /u/youali
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